Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Revealing RNA virus diversity and evolution in unicellular algae transcriptomes

View through CrossRef
Abstract Remarkably little is known about the diversity and evolution of RNA viruses in unicellular eukaryotes. We screened a total of 570 transcriptomes from the Marine Microbial Eukaryote Transcriptome Sequencing Project that encompasses a wide diversity of microbial eukaryotes, including most major photosynthetic lineages (i.e. the microalgae). From this, we identified thirty new and divergent RNA virus species, occupying a range of phylogenetic positions within the overall diversity of RNA viruses. Approximately one-third of the newly described viruses comprised single-stranded positive-sense RNA viruses from the order Lenarviricota associated with fungi, plants, and protists, while another third were related to the order Ghabrivirales, including members of the protist and fungi-associated Totiviridae. Other viral species showed sequence similarity to positive-sense RNA viruses from the algae-associated Marnaviridae, the double-stranded RNA (ds-RNA) Partitiviridae, as well as tentative evidence for one negative-sense RNA virus related to the Qinviridae. Importantly, we were able to identify divergent RNA viruses from distant host taxa, revealing the ancestry of these viral families and greatly extending our knowledge of the RNA viromes of microalgal cultures. Both the limited number of viruses detected per sample and the low sequence identity to known RNA viruses imply that additional microalgal viruses exist that could not be detected at the current sequencing depth or were too divergent to be identified using sequence similarity. Together, these results highlight the need for further investigation of algal-associated RNA viruses as well as the development of new tools to identify RNA viruses that exhibit very high levels of sequence divergence.
Title: Revealing RNA virus diversity and evolution in unicellular algae transcriptomes
Description:
Abstract Remarkably little is known about the diversity and evolution of RNA viruses in unicellular eukaryotes.
We screened a total of 570 transcriptomes from the Marine Microbial Eukaryote Transcriptome Sequencing Project that encompasses a wide diversity of microbial eukaryotes, including most major photosynthetic lineages (i.
e.
the microalgae).
From this, we identified thirty new and divergent RNA virus species, occupying a range of phylogenetic positions within the overall diversity of RNA viruses.
Approximately one-third of the newly described viruses comprised single-stranded positive-sense RNA viruses from the order Lenarviricota associated with fungi, plants, and protists, while another third were related to the order Ghabrivirales, including members of the protist and fungi-associated Totiviridae.
Other viral species showed sequence similarity to positive-sense RNA viruses from the algae-associated Marnaviridae, the double-stranded RNA (ds-RNA) Partitiviridae, as well as tentative evidence for one negative-sense RNA virus related to the Qinviridae.
Importantly, we were able to identify divergent RNA viruses from distant host taxa, revealing the ancestry of these viral families and greatly extending our knowledge of the RNA viromes of microalgal cultures.
Both the limited number of viruses detected per sample and the low sequence identity to known RNA viruses imply that additional microalgal viruses exist that could not be detected at the current sequencing depth or were too divergent to be identified using sequence similarity.
Together, these results highlight the need for further investigation of algal-associated RNA viruses as well as the development of new tools to identify RNA viruses that exhibit very high levels of sequence divergence.

Related Results

B-247 BLADE-R: streamlined RNA extraction for clinical diagnostics and high-throughput applications
B-247 BLADE-R: streamlined RNA extraction for clinical diagnostics and high-throughput applications
Abstract Background Efficient nucleic acid extraction and purification are crucial for cellular and molecular biology research, ...
Prevalence of Hepatitis C Virus Infection in Hemodialysis Patients: A Longitudinal Study Comparing the Results of RNA and Antibody Assays
Prevalence of Hepatitis C Virus Infection in Hemodialysis Patients: A Longitudinal Study Comparing the Results of RNA and Antibody Assays
We longitudinally studied 51 patients from two hemodialysis centers to determine the prevalence of hepatitis C virus infection in hemodialysis patients. Serum samples were tested f...
Detection of Multiple Types of Cancer Driver Mutations Using Targeted RNA Sequencing in NSCLC
Detection of Multiple Types of Cancer Driver Mutations Using Targeted RNA Sequencing in NSCLC
ABSTRACTCurrently, DNA and RNA are used separately to capture different types of gene mutations. DNA is commonly used for the detection of SNVs, indels and CNVs; RNA is used for an...
Accurate in silico predictions of modified RNA interactions to a prototypical RNA-binding protein with λ-dynamics
Accurate in silico predictions of modified RNA interactions to a prototypical RNA-binding protein with λ-dynamics
RNA-binding proteins shape biology through their widespread functions in RNA biochemistry. Their function requires the recognition of specific RNA motifs for targeted binding. Thes...
Ordered release of genomic RNA during icosahedral virus disassembly
Ordered release of genomic RNA during icosahedral virus disassembly
AbstractTo release their genomic cargo, many icosahedral viruses undergo a series of ordered conformational changes via distinct disassembly intermediates that allow nucleic acid e...
Capítulo 6 – HIV-AIDS, como tratar, o que fazer e o que não fazer durante o tratamento?
Capítulo 6 – HIV-AIDS, como tratar, o que fazer e o que não fazer durante o tratamento?
A infecção pelo vírus do HIV pode ocorrer de diversas maneiras, tendo sua principal forma a via sexual por meio do sexo desprotegido. O vírus do HIV fica em um período de incubação...
Automatic Identification of Harmful Algae Based On Multiple Convolutional Neural Networks and Transfer Learning
Automatic Identification of Harmful Algae Based On Multiple Convolutional Neural Networks and Transfer Learning
Abstract The monitoring of harmful algae is very important for the maintenance of the aquatic ecological environment. Traditional algae monitoring methods require professio...

Back to Top